Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry. Multi-omics approaches enable the comprehensive investigation of the complex interactions between multiple layers of information to provide a more holistic view of disease pathogenesis. Therefore, this study investigated the genomic and epigenomic signatures and the possible regulatory mechanisms underlying subclinical mastitis by integrating RNA sequencing data (mRNA and lncRNA), small RNA sequencing data (miRNA) and DNA methylation sequencing data of milk somatic cells from 10 healthy cows and 20 cows with naturally occurring subclinical mastitis caused by Staphylococcus aureus or Staphylococcus chromogenes. Functional investigation of the data sets through gene set analysis uncovered 3458 biological process GO terms and 170 KEGG pathways with altered activities during subclinical mastitis, provided further insights into subclinical mastitis and revealed the involvement of multi-omics signatures in the altered immune responses and impaired mammary gland productivity during subclinical mastitis. The abundant genomic and epigenomic signatures with significant alterations related to subclinical mastitis were observed, including 30,846, 2552, 1276 and 57 differential methylation haplotype blocks (dMHBs), differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs), respectively. Next, 5 factors presenting the principal variation of differential multi-omics signatures were identified. The important roles of Factor 1 (DEG, DEM and DEL) and Factor 2 (dMHB and DEM), in the regulation of immune defense and impaired mammary gland functions during subclinical mastitis were revealed. Each of the omics within Factors 1 and 2 explained about 20% of the source of variation in subclinical mastitis. Also, networks of important functional gene sets with the involvement of multi-omics signatures were demonstrated, which contributed to a comprehensive view of the possible regulatory mechanisms underlying subclinical mastitis. Furthermore, multi-omics integration enabled the association of the epigenomic regulatory factors (dMHBs, DELs and DEMs) of altered genes in important pathways, such as ‘Staphylococcus aureus infection pathway’ and ‘natural killer cell mediated cytotoxicity pathway’, etc., which provides further insights into mastitis regulatory mechanisms. Moreover, few multi-omics signatures (14 dMHBs, 25 DEGs, 18 DELs and 5 DEMs) were identified as candidate discriminant signatures with capacity of distinguishing subclinical mastitis cows from healthy cows. The integration of genomic and epigenomic data by multi-omics approaches in this study provided a better understanding of the molecular mechanisms underlying subclinical mastitis and identified multi-omics candidate discriminant signatures for subclinical mastitis, which may ultimately lead to the development of more effective mastitis control and management strategies.

中文翻译：

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多组学整合确定了牛亚临床乳腺炎的调控因素

由多种因素引起的乳腺炎仍然是乳制品行业最常见和最昂贵的疾病之一。多组学方法能够全面研究多层信息之间复杂的相互作用，从而提供疾病发病机制的更全面的视图。因此，本研究通过整合10头健康奶牛乳体细胞的RNA测序数据（mRNA和lncRNA）、小RNA测序数据（miRNA）和DNA甲基化测序数据，研究了亚临床乳腺炎的基因组和表观基因组特征以及可能的调控机制。 20 头患有由金黄色葡萄球菌或产色葡萄球菌引起的自然发生的亚临床乳腺炎的奶牛。通过基因集分析对数据集进行功能研究，发现了 3458 个生物过程 GO 术语和 170 个 KEGG 通路，这些通路在亚临床乳腺炎期间活动发生了改变，为亚临床乳腺炎提供了进一步的见解，并揭示了多组学特征与免疫反应改变和乳房受损的关系亚临床乳腺炎期间的腺体生产力。观察到与亚临床乳腺炎相关的具有显着改变的丰富基因组和表观基因组特征，分别包括 30,846、2552、1276 和 57 个差异甲基化单倍型块（dMHB）、差异表达基因（DEG）、lncRNA（DEL）和 miRNA（DEM） 。接下来，确定了代表差异多组学特征主要变异的 5 个因素。揭示了因子 1（DEG、DEM 和 DEL）和因子 2（dMHB 和 DEM）在亚临床乳腺炎期间调节免疫防御和受损乳腺功能中的重要作用。因素 1 和因素 2 中的每个组学都解释了亚临床乳腺炎变异来源的约 20%。此外，还证明了涉及多组学特征的重要功能基因组网络，这有助于全面了解亚临床乳腺炎潜在的调控机制。此外，多组学整合使得重要途径中改变基因的表观基因组调控因子（dMHB、DEL和DEM）能够关联起来，例如“金黄色葡萄球菌感染途径”和“自然杀伤细胞介导的细胞毒性途径”等，这使得提供了对乳腺炎调节机制的进一步见解。此外，很少有多组学特征（14 dMHB、25 DEG、18 DEL 和 5 DEM）被确定为能够区分亚临床乳腺炎奶牛和健康奶牛的候选判别特征。本研究通过多组学方法整合基因组和表观基因组数据，使人们更好地了解亚临床乳腺炎的分子机制，并确定了亚临床乳腺炎的多组学候选判别特征，这可能最终导致开发更有效的乳腺炎控制方法和管理策略。